scholarly journals Image Tone Mapping for an HDR Image by Adoptive Global tone-mapping algorithm

Author(s):  
Subodh Prakash Tiwari ◽  
Ashutosh Shrivastava
Author(s):  
Yuan Jia ◽  
Wenting Zhang

The recognition rate of computer vision algorithms is highly dependent on the image quality. To enhance the visual quality of the images captured under high-dynamic range (HDR) scenes, we propose an efficient and adaptive tone mapping algorithm based on guided image filter (GIF). The HDR image is compressed adaptively according to its average luminance. Then we decompose it into a base layer and a detail layer using the guided image filter. We improve the base layer and enhance the detail layer simultaneously, and combine the two layers to get the final low-dynamic range (LDR) image. Since the parameters are linked with image statistics, they adaptively fit to various kinds of images. The objective evaluation results on HDR image sets demonstrate the superiority of our proposed algorithm. Meanwhile, the result of our algorithm can reduce the halo artifacts and preserve more detail by subjective observation.


2017 ◽  
Author(s):  
Weiwei Duan ◽  
Huinan Guo ◽  
Zuofeng Zhou ◽  
Huimin Huang ◽  
Jianzhong Cao

2016 ◽  
Vol 16 (4) ◽  
pp. 1317-1333 ◽  
Author(s):  
Prasoon Ambalathankandy ◽  
Alain Horé ◽  
Orly Yadid-Pecht

Author(s):  
Toshiyuki Dobashi ◽  
Atsushi Tashiro ◽  
Masahiro Iwahashi ◽  
Hitoshi Kiya

A tone mapping operation (TMO) for HDR images with fixed-point arithmetic is proposed. A TMO generates a low dynamic range (LDR) image from a high dynamic range (HDR) image by compressing its dynamic range. Since HDR images are generally expressed in a floating-point data format, a TMO also deals with floating-point data even though resulting LDR images have integer data. As a result, conventional TMOs require many resources such as computational and memory cost. To reduce the resources, an integer TMO which treats a floating-point number as two 8-bit integer numbers was proposed. However, this method has the limitation of available input HDR image formats. The proposed method introduces an intermediate format to relieve the limitation of input formats, and expands the integer TMO for the intermediate format. The proposed integer TMO can be applied for multiple formats such as the RGBE and the OpenEXR. Moreover, the method can conduct all calculations in the TMO with fixed-point arithmetic. Using both integer data and fixed-point arithmetic, the method reduces not only the memory cost, but also the computational cost. The experimental and evaluation results show that the proposed method reduces the computational and memory cost, and gives almost same quality of LDR images, compared with the conventional method with floating-point arithmetic.


2011 ◽  
Vol 57 (4) ◽  
pp. 1807-1814 ◽  
Author(s):  
Kyungman Kim ◽  
Jonghyun Bae ◽  
Jaeseok Kim
Keyword(s):  

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